Detection and characterization of channel systems provide valuable geological information about earth's surfaces or sub-surfaces. For example, stream systems on a land or on a seafloor provide information about the changes in those streams and their surroundings throughout their geological evolution.
Various techniques exist for imaging segments of channel systems in plan view. These techniques include seismic imaging, digital topography including digital elevation models (DEMs), and air photos. These imaging techniques can result in high resolution images, from which information can be derived about various properties such as the elevation (height or depth), or rock structure of various segments of the channel system. Some imaging techniques can provide a resolution of several data points per square meter. The imaging techniques, however, often show segments of a channel system that distinctly differ from their surroundings and often do not clearly connect to other segments. The image, therefore, may look to a user as a network of disconnected segments. Moreover, the imaging technique does not provide quantitative information related to characteristics of the channel system, such as its age, drainage area, or smoothness.
Accurate and reproducible techniques have been lacking detecting or connecting various segments of channels. Existing techniques often use visual methods in which a user inspects an image or the corresponding data and outlines the possible boundaries of segments of a channel system or connects those segments to form the entire channel system. These techniques are often inaccurate, inefficient, and irreproducible, because they depend on an objective judgment of the user.
Therefore, what is needed is an efficient, reproducible, and automated technique for the detection and characterization of channel systems based on imaging data sets of various types.